Development and validation of a cardiovascular risk prediction model for Sri Lankans using machine learning.

ABSTRACT:

Introduction and objectives

Sri Lankans do not have a specific cardiovascular (CV) risk prediction model and therefore, World Health Organization(WHO) risk charts developed for the Southeast Asia Region are being used. We aimed to develop a CV risk prediction model specific for Sri Lankans using machine learning (ML) of data of a population-based, randomly selected cohort of Sri Lankans followed up for 10 years and to validate it in an external cohort.

Material and methods

The cohort consisted of 2596 individuals between 40-65 years of age in 2007, who were followed up for 10 years. Of them, 179 developed hard CV diseases (CVD) by 2017. We developed three CV risk prediction models named model 1, 2 and 3 using ML. We compared predictive performances between models and the WHO

SUBMITTER: Mettananda C 

PROVIDER: S-EPMC11495576 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature